搜索资源列表
envec.py
- 识别中文，对中文词进行统计，打印出每个中文词的数目。-Identify Chinese, the Chinese word for statistics, print out the number of each Chinese word.
numdect.py
- 汉字月份识别与转换为数字月份，特殊：含有十的汉字的处理-Character recognition and converted to digital in February month, special: contains characters deal with ten
SpeechRec
- 基于Matlab的语音识别系统，实现了基本的算法，具有较高的参考价值。-Matlab-based speech recognition system to achieve the basic algorithm, has a high reference value.
myvqfig
- 基于VQ的特定人的小词汇量的语音识别系统，能够识别普通词汇，例如0，1，大学。-Based on VQ of someone s small vocabulary speech recognition system, able to identify common words, such as 0, 1, university.
hanzitongji
- 汉字字频统计的小程序，使用前需要修改源码中的读取路径，另外txt必须Unicode编码才能识别。-Chinese characters word frequency statistics applets, you need to modify the source code (the read path) before using. Additionally, the Unicode encoding txt must be identified.
LDA
- 使用LDA算法对OPC人脸数据库进行识别，并判断识别的准确度-LDA algorithm using OPC face to identify and determine the accuracy of recognition
Speech-Recognition-System
- 本文介绍了基于MATLAB的语音识别系统，包括对语音信号的特征提取，包括语音信号的特征提取，快速傅立叶变换，离散余弦转换，线性预测分析，梅尔频率倒谱系数以及高斯混合模型。-This paper aims at development and performance analysis of a speaker dependent speech recognition system using MATLAB® . The issues that were considered are 1
CRFPP-0.53-
- CRF++-0.53,条件随机场命名实体识别，0.53版本，顺利通过测试运行--0.53 CRF, conditional random field named entity recognition, 0.53 version, successfully passed the test run
Windows_voice_1.109_57283e23
- 科大讯飞语音识别最新Demo,国内优秀的语音识别平台-new demo
yuyinshibie
- 基于dtw的语音识别系统，已经测试过，可直接拿来用，但识别率不是太高，只有80 多-Speech recognition system based on DTW, has been tested, can be used directly, but the recognition rate is not too high, only more than 80
bp---Data-Classification
- 对几种流行音乐音乐的特征值用BP神经网络进行识别分类并求其正确率，对初学者有用-Several popular music for the identification and classification feature values and for its accuracy BP neural network, useful for beginners
perceptron-for-NER
- 一个中文NER工具，可以实现利用感知机的命名实体识别，效果比较好，大概在0.82左右- U4E00 u4E2A u4E2D u6587NER u5DE5 u5177 uFF0C u53EF u4EE5 u5B9E u73B0 u5229 u7528 u611F u77E5 u673A u7684 u547D u540D u5B9E u4F53 u8BC6 u522B uFF0C u6548 u679C u6BD4 u8F83 u597D
parsing
- 句法分析（syntactic parsing）的任务就是识别句子的句法结构（syntactic structure）。在自然语言处理领域，句法分析的目标是实现高正确率、高鲁棒性、高速度的自动句法分析过程。 但是该问题的困难在于自然语言中存在大量的结构歧义（structural ambuguity）。例如：I saw a boy in the park.这句话有两种可能的句法分析方法：1、[I saw a boy] in the park.2、I saw a [boy in the park].语